Comparison between different neoadjuvant chemotherapy regimens and local therapy alone for bladder cancer: a systematic review and network meta-analysis of oncologic outcomes
Bibliographic record
Abstract
PURPOSE: The present systematic review and network meta-analysis (NMA) compared the current different neoadjuvant chemotherapy (NAC) regimes for bladder cancer patients to rank them. METHODS: We used the Bayesian approach in NMA of six different therapy regimens cisplatin, cisplatin/doxorubicin, (gemcitabine/cisplatin) GC, cisplatin/methotrexate, methotrexate, cisplatin, and vinblastine (MCV) and (MVAC) compared to locoregional treatment. RESULTS: Fifteen studies comprised 4276 patients who met the eligibility criteria. Six different regimes were not significantly associated with a lower likelihood of overall mortality rate compared to local treatment alone. In progression-free survival (PFS) rates, cisplatin, GC, cisplatin/methotrexate, MCV and MVAC were not significantly associated with a higher likelihood of PFS rate compared to locoregional treatment alone. In local control outcome, MCV, MVAC, GC and cisplatin/methotrexate were not significantly associated with a higher likelihood of local control rate versus locoregional treatment alone. Nevertheless, based on the analyses of the treatment ranking according to SUCRA, it was highly likely that MVAC with high certainty of results appeared as the most effective approach in terms of mortality, PFS and local control rates. GC and cisplatin/doxorubicin with low certainty of results was found to be the best second options. CONCLUSION: No significant differences were observed in mortality, progression-free survival and local control rates before and after adjusting the type of definitive treatment in any of the six study arms. However, MVAC was found to be the most effective regimen with high certainty, while cisplatin alone and cisplatin/methotrexate should not be recommended as a neoadjuvant chemotherapy regime.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.043 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".